I am currently working on a number of research projects dealing with information visualization, with applications in fields like the digital humanities, virology, and psychology. Some example research topics include:

• Ethical and Deceptive Visualization: visualizations are sometimes our first, most impactful, or only interaction with data. This makes visualizations potentially very powerful. Wherever there is power, there is a potential for harm and misuse. I am interested in the ethical considations around visualization, both in terms of how specific visualizations can mislead or bias, but in an overall sense of designing best practices for visualization designers. This work involves reflections on the state of the field, case studies of specific systems, and empirical studies on visualization designs.

  Example papers:
  Ethical Dimensions of Visualization Research
  Truncating the Y-Axis: Threat or Menace?

• Visual Statistics: If we know what someone wants from our data, then we can give them that information directly. In this case a database query might be more suitable than a visualization tool. But the promise of visualization lies in situations where the designer may not know exactly what the viewer wants to know, but the viewer is instead free to explore the dataset to build up understanding by themselves. In order for such designs to work, we as designers need to know how good users are at using visual information to build up big picture statistical information from data.

  Research from pyschology has shown that the visual system is capable of extracting a wide variety of statistical information (average values, variability, extrema) from visual stimuli in the world around us. My research in this area is an attempt to apply these findings to visualization, to show how we can design displays that rely on these abilities to let viewers build up "big pictures" by themselves.

  Example papers:
  Looks Good To Me: Visualizations as Sanity Checks
  Regression by Eye: Estimating Trends in Bivariate Visualizations

• Systems Building in Applied Domains: the relationship that specific domains have with data is changing, as a result not just of "more" data, but different data. My expertise with uncertainty visualization, epistemology, and human computer interaction has led me to work with experts in diverse fields like the digitial humanities, genomics, and business intelligence to to solve data problems that have been overlooked by conventional visualization systems.

  Example papers:
  Exploring Collections of Tagged Text for Literary Scholarship
  Visualizing Virus Population Variability From Next Generation Sequencing Data

Email: m.correll_at_northeastern.edu

Last updated 31 January 2024